ArticleSchizophrenia research2022
Perceptual pathways to hallucinogenesis.
Article in Schizophrenia research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
12 citing papers in PubMed.
- Errors or Adaptations? A Critical Review of Predictive Processing in Psychiatry.Behavioral sciences (Basel, Switzerland) · 2026Review
- Compensatory hallucinogenesis across three neuropsychiatric disorders: a Bayesian account.Brain communications · 2026Review
- Refining mechanistic models of hallucinations for enhanced translatability.Translational psychiatry · 2025Review
- Emergence and Dynamics of Delusions and Hallucinations Across Stages in Early Psychosis.Biological psychiatry · 2025Article
- When perception meets grief: how the brain reconstructs person networks in response to absence.Social cognitive and affective neuroscience · 2025Article
- A Computational Account of the Development and Evolution of Psychotic Symptoms.Biological psychiatry · 2025Review
- The Future of Perceptual Dysregulation in Psychiatric Nosology.Current topics in behavioral neurosciences · 2025Review
- Recent social stress and severity of auditory hallucinations.Schizophrenia research · 2024Article
- Article
- Evidence for Reduced Sensory Precision and Increased Reliance on Priors in Hallucination-Prone Individuals in a General Population Sample.Schizophrenia bulletin · 2024Article
- A novel computational approach to pain perception modelling within a Bayesian framework using quantitative sensory testing.Scientific reports · 2023Article
- A computational lens on menopause-associated psychosis.Frontiers in psychiatry · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Recent advances in computational psychiatry have provided unique insights into the neural and cognitive underpinnings of psychotic symptoms. In particular, a host of new data has demonstrated the utility of computational frameworks for understanding how hallucinations might arise from alterations in typical perceptual processing. Of particular promise are models based in Bayesian inference that link hallucinatory perceptual experiences to latent states that may drive them. In this piece, we move beyond these findings to ask: how and why do these latent states arise, and how might we take advantage of heterogeneity in that process to develop precision approaches to the treatment of hallucinations? We leverage specific models of Bayesian inference to discuss components that might lead to the development of hallucinations. Using the unifying power of our model, we attempt to place disparate findings in the study of psychotic symptoms within a common framework. Finally, we suggest directions for future elaboration of these models in the service of a more refined psychiatric nosology based on predictable, testable, and ultimately treatable information processing derangements.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.